Clinical context and challenges of peri-implant diagnosis

The long-term success of implant rehabilitations is currently threatened by the increasing prevalence of peri-implant diseases. Current diagnosis, based on clinical and radiographic parameters, often occurs late, once tissue destruction is already established. While the IDRA (Implant Disease Risk Assessment) tool provides an initial structured risk stratification (Bleeding on probing, pocket depth, periodontal history), clinicians face the need to integrate new risk vectors to improve prevention and implant longevity.

Objective and hypotheses of the study

This study aims to evaluate the evolution of risk analysis models, such as IDRA, by integrating emerging determinants from contemporary literature. The specific objective is to analyse the impact of biomechanical factors (occlusal overload), tribocorrosion phenomena (release of titanium particles) and molecular biomarkers on peri-implant bone stability.

The tested hypothesis suggests that peri-implant stability does not solely depend on classical biological variables, but results from a complex interaction between functional loads, the immune response to metallic wear particles, and the levels of active biomarkers, such as aMMP-8 in the sulcular fluid. Integrating these data would enable a transition from an observational diagnosis to a precision medicine approach.

Analysis of peri-implant risk stratification protocols

The analysis is based on the examination of the Implant Disease Risk Assessment (IDRA) model, a structured tool designed for the risk stratification of peri-implant diseases. The study evaluates the integration of multiple clinical and biological vectors to prevent late implant failure.

The clinical parameters analysed within the IDRA model include:

• The percentage of bleeding on probing (BOP%).
• The prevalence of sites with a probing depth (PD) ≥ 5 mm.
• The relationship between periodontal bone loss and the patient's age.
• Susceptibility to periodontitis, defined according to the 2017 international classification.
• The frequency of supportive periodontal therapy (SPT).
• Prosthetic factors and oral hygiene indicators.

The assessment also incorporates biomechanical determinants, such as occlusal overload (non-axial forces or forces concentrated on a limited number of implants), and indicators of material degradation related to the implant-abutment complex. Furthermore, the analysis focuses on specific sulcular fluid biomarkers identified as diagnostic tools: type I collagen levels, cross-linked N-terminal telopeptide and calprotectin. These data aim to complement conventional radiographic and clinical parameters to enable earlier diagnosis.

Towards a comprehensive assessment framework: beyond the IDRA model

The synthesis of current data confirms that the IDRA (Implant Disease Risk Assessment) model constitutes the reference standard for peri-implant risk stratification. However, the analysis highlights the need to evolve towards a more comprehensive framework integrating biomechanical and biological variables previously considered secondary.

Clinical and periodontal risk vectors (IDRA Model)

The IDRA model is based on the integration of several clinical vectors whose critical thresholds are identified as follows:

Emerging factors and biomarkers

The study identifies determining co-factors that modulate marginal bone stability and which must now be integrated into precision diagnosis:

• Biomechanical determinants: Occlusal overload, particularly non-axial forces or those concentrated on a limited number of implants, is correlated with increased marginal bone loss, especially in the presence of pre-existing biofilm-induced inflammation.
• Tribocorrosion and metallic particles: High levels of titanium particles and corrosion products have been detected specifically at sites affected by peri-implantitis. These products act as amplifiers of the tissue inflammatory response.
• Fluid biomarkers (Salivomics): The use of active MMP-8 (aMMP-8) in peri-implant sulcular fluid stands out as an early diagnostic tool. Elevated levels of aMMP-8 are directly associated with an increased risk of tissue destruction even before the appearance of radiographic signs.

These results indicate that long-term implant stability depends on the balance between biological (biofilm), mechanical (occlusion) and material (tribocorrosion) factors, necessitating an update of current risk models towards a precision medicine approach.

Analysis of the transition towards a multidimensional assessment

The IDRA (Implant Disease Risk Assessment) model represents a major advancement in peri-implant risk stratification. However, this study highlights that traditional diagnosis — relying on bleeding on probing (BOP), pocket depth and radiographic bone loss — often occurs at a stage of already established tissue destruction. The clinical challenge is now shifting towards the early identification of cofactors likely to amplify biofilm-induced inflammation.

The integration of occlusal load as a predictive variable is fundamental here. Although its direct causal role in peri-implantitis remains debated, data indicate that non-axial traumatic forces act as modulators of marginal bone stability. For the practitioner, this means that occlusion management must not be treated independently of the biological health of peri-implant tissues.

Furthermore, the study highlights the importance of material-related factors, particularly tribocorrosion phenomena at the implant-abutment interface. The release of titanium particles and corrosion products into the peri-implant tissues is no longer considered an epiphenomenon: these particles act as pro-inflammatory agents altering bone metabolism. This perspective reinforces the value of precision medicine and the use of biomarkers such as aMMP-8 (active MMP-8) in the sulcular fluid for more precise monitoring than a simple clinical examination.

In practical terms, for the practitioner:

• Detecting overload: Integrate the assessment of non-axial occlusal forces into your monitoring, as these mechanical stresses can modulate bone stability beyond biological factors alone.
• Monitor tribocorrosion: Be vigilant regarding wear at the implant-abutment interface; the released metal particles promote a local inflammatory response in predisposed patients.
• Personalise the risk: Use the IDRA diagram for clinical stratification, while weighting it by the prosthetic specificities and the patient's periodontal susceptibility profile (2017 classification).

Technical glossary of the study

IDRA (Implant Disease Risk Assessment): Structured risk stratification system for peri-implant diseases. It synthesises clinical vectors such as the percentage of bleeding on probing, pocket depth, periodontal susceptibility (2017 classification) and maintenance parameters.

BOP% (Bleeding on Probing): Bleeding on probing index expressed as a percentage. This parameter is used as a key indicator of local inflammatory activity within peri-implant risk assessment models.

SPT (Supportive Periodontal Therapy) : Supportive periodontal therapy. The regularity of this professional maintenance is a determining factor integrated into the IDRA diagram to prevent the onset of peri-implantitis.

Sulcular biomarkers: Biological indicators, such as calprotectin or type I collagen, measured in the crevicular fluid. Their analysis aims at the early detection of tissue destruction, often before the appearance of radiographic signs.

Non-axial forces: Occlusal loads exerted outside the longitudinal axis of the implant. They are considered risk co-factors that can exacerbate marginal bone loss in the presence of biofilm-induced inflammation.

Peri-implant mucositis: Reversible inflammatory reaction affecting only the soft tissues surrounding a functioning implant. It constitutes the clinical precursor stage of peri-implantitis, where bone destruction is absent.

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